.TH "gdal_pansharpen" 1 "Mon Apr 25 2016" "GDAL" \" -*- nroff -*-
.ad l
.nh
.SH NAME
gdal_pansharpen \- gdal_pansharpen\&.py 
Perform a pansharpen operation\&.
.PP
(Since GDAL 2\&.1)
.SH "SYNOPSIS"
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.nf
gdal_pansharpen [--help-general] pan_dataset {spectral_dataset[,band=num]}+ out_dataset
                [-of format] [-b band]* [-w weight_val]*
                [-r {nearest,bilinear,cubic,cubicspline,lanczos,average}]
                [-threads {ALL_CPUS|number}] [-bitdepth val] [-nodata val]
                [-spat_adjust {union,intersection,none,nonewithoutwarning}]
                [-co NAME=VALUE]* [-q]
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.SH "DESCRIPTION"
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The gdal_pansharpen\&.py script performs a pan-sharpening operation\&. It can create a 'classic' output dataset (such as GeoTIFF), or a VRT dataset describing the pan-sharpening operation\&.
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More details can be found in the \fCVRT tutorial\fP\&.
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.IP "\fB\fB-of\fP \fIformat\fP:\fP" 1c
Select the output format\&. The default is GeoTIFF (GTiff)\&. 'VRT' can also be used\&. Use the short format name\&. 
.IP "\fB\fB-b\fP \fIband\fP:\fP" 1c
Select band \fIband\fP from the input spectral bands for output\&. Bands are numbered from 1 in the order spectral bands are specified\&. Multiple \fB-b\fP switches may be used\&. When no -b switch is used, all input spectral bands are set for output\&. 
.IP "\fB\fB-w\fP \fIweight_val\fP:\fP" 1c
Specify a weight for the computation of the pseudo panchromatic value\&. There must be as many -w switches as input spectral bands\&. 
.IP "\fB\fB-r\fP \fI{nearest,bilinear,cubic (default),cubicspline,lanczos,average}\fP:\fP" 1c
Select a resampling algorithm\&. 
.IP "\fB\fB-threads\fP \fI{ALL_CPUS,number}\fP:\fP" 1c
Specify number of threads to use to do the resampling and pan-sharpening itself\&. Can be an integer number or ALL_CPUS\&. 
.IP "\fB\fB-bitdepth\fP \fIval\fP:\fP" 1c
Specify the bit depth of the panchromatic and spectral bands (e\&.g\&. 12)\&. If not specified, the NBITS metadata item from the panchromatic band will be used if it exists\&. 
.IP "\fB\fB-nodata\fP \fIval\fP:\fP" 1c
Specify nodata value for bands\&. Used for the resampling and pan-sharpening computation itself\&. If not set, deduced from the input bands, provided they have a consistent setting\&. 
.IP "\fB\fB-spat_adjust\fP \fI{union (default),intersection,none,nonewithoutwarning}\fP:\fP" 1c
Select behaviour when bands have not the same extent\&. See \fISpatialExtentAdjustment\fP documentation in \fCVRT tutorial\fP 
.IP "\fB\fB-co\fP \fI'NAME=VALUE'\fP:\fP" 1c
Passes a creation option to the output format driver\&. Multiple \fB-co\fP options may be listed\&. See format specific documentation for legal creation options for each format\&. 
.IP "\fB\fB-q\fP:\fP" 1c
Suppress progress monitor and other non-error output\&. 
.IP "\fB\fIpan_dataset\fP\fP" 1c
Dataset with panchromatic band (first band will be used)\&. 
.IP "\fB\fIspectral_dataset[,band=num]\fP\fP" 1c
Dataset with one or several spectral bands\&. If the band option is not specified, all bands of the datasets are taken into account\&. Otherwise, only the specified (num)th band\&. The same dataset can be repeated several times\&. 
.IP "\fB\fIout_dataset\fP\fP" 1c
Output dataset 
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Bands should be in the same projection\&.
.SH "EXAMPLE"
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With spectral bands in a single dataset : 
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gdal_pansharpen.py panchro.tif multispectral.tif pansharpened_out.tif

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With a few spectral bands from a single dataset, reordered : 
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gdal_pansharpen.py panchro.tif multispectral.tif,band=3 multispectral.tif,band=2 multispectral.tif,band=1 pansharpened_out.tif

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With spectral bands in several datasets : 
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gdal_pansharpen.py panchro.tif band1.tif band2.tif band3.tif pansharpened_out.tif

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Specify weights: 
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gdal_pansharpen.py -w 0.7 -w 0.2 -w 0.1 panchro.tif multispectral.tif pansharpened_out.tif

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Specify RGB bands from a RGBNir multispectral dataset while computing the pseudo panchromatic intensity on the 4 RGBNir bands: 
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gdal_pansharpen.py -b 1 -b 2 -b 3 panchro.tif rgbnir.tif pansharpened_out.tif

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.SH "AUTHORS"
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Even Rouault <even\&.rouault at spatialys\&.com> 
